Dataset statistics
| Number of variables | 11 |
|---|---|
| Number of observations | 886 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 58.1 KiB |
| Average record size in memory | 67.1 B |
Variable types
| Numeric | 6 |
|---|---|
| Categorical | 5 |
df_index is highly correlated with PassengerId | High correlation |
PassengerId is highly correlated with df_index | High correlation |
Survived is highly correlated with Sex_male | High correlation |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Embarked_Q is highly correlated with Embarked_S | High correlation |
Embarked_S is highly correlated with Embarked_Q | High correlation |
Sex_male is highly correlated with Survived | High correlation |
df_index is highly correlated with PassengerId | High correlation |
PassengerId is highly correlated with df_index | High correlation |
Survived is highly correlated with Sex_male | High correlation |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Embarked_Q is highly correlated with Embarked_S | High correlation |
Embarked_S is highly correlated with Embarked_Q | High correlation |
Sex_male is highly correlated with Survived | High correlation |
df_index is highly correlated with PassengerId | High correlation |
PassengerId is highly correlated with df_index | High correlation |
Survived is highly correlated with Sex_male | High correlation |
Pclass is highly correlated with Fare | High correlation |
Fare is highly correlated with Pclass | High correlation |
Embarked_Q is highly correlated with Embarked_S | High correlation |
Embarked_S is highly correlated with Embarked_Q | High correlation |
Sex_male is highly correlated with Survived | High correlation |
Sex_male is highly correlated with Survived | High correlation |
Survived is highly correlated with Sex_male | High correlation |
df_index is highly correlated with PassengerId | High correlation |
PassengerId is highly correlated with df_index | High correlation |
Survived is highly correlated with Sex_male | High correlation |
Pclass is highly correlated with Fare | High correlation |
SibSp is highly correlated with Parch | High correlation |
Parch is highly correlated with SibSp | High correlation |
Fare is highly correlated with Pclass | High correlation |
Embarked_Q is highly correlated with Embarked_S | High correlation |
Embarked_S is highly correlated with Embarked_Q | High correlation |
Sex_male is highly correlated with Survived | High correlation |
df_index is uniformly distributed | Uniform |
PassengerId is uniformly distributed | Uniform |
df_index has unique values | Unique |
PassengerId has unique values | Unique |
SibSp has 603 (68.1%) zeros | Zeros |
Parch has 674 (76.1%) zeros | Zeros |
Reproduction
| Analysis started | 2022-06-19 05:57:11.989948 |
|---|---|
| Analysis finished | 2022-06-19 05:57:28.828808 |
| Duration | 16.84 seconds |
| Software version | pandas-profiling v3.2.0 |
| Download configuration | config.json |
df_index
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONUNIFORMUNIQUE| Distinct | 886 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 444.6173815 |
| Minimum | 0 |
|---|---|
| Maximum | 890 |
| Zeros | 1 |
| Zeros (%) | 0.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 44.25 |
| Q1 | 222.25 |
| median | 444.5 |
| Q3 | 665.75 |
| 95-th percentile | 845.75 |
| Maximum | 890 |
| Range | 890 |
| Interquartile range (IQR) | 443.5 |
Descriptive statistics
| Standard deviation | 257.0487858 |
|---|---|
| Coefficient of variation (CV) | 0.578134811 |
| Kurtosis | -1.195429246 |
| Mean | 444.6173815 |
| Median Absolute Deviation (MAD) | 222 |
| Skewness | 0.002397173832 |
| Sum | 393931 |
| Variance | 66074.0783 |
| Monotonicity | Strictly increasing |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0 | 1 | 0.1% |
| 597 | 1 | 0.1% |
| 586 | 1 | 0.1% |
| 587 | 1 | 0.1% |
| 588 | 1 | 0.1% |
| 589 | 1 | 0.1% |
| 590 | 1 | 0.1% |
| 591 | 1 | 0.1% |
| 592 | 1 | 0.1% |
| 593 | 1 | 0.1% |
| Other values (876) | 876 |
| Value | Count | Frequency (%) |
| 0 | 1 | |
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 |
| Value | Count | Frequency (%) |
| 890 | 1 | |
| 889 | 1 | |
| 888 | 1 | |
| 887 | 1 | |
| 886 | 1 | |
| 885 | 1 | |
| 884 | 1 | |
| 883 | 1 | |
| 882 | 1 | |
| 881 | 1 |
PassengerId
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONUNIFORMUNIQUE| Distinct | 886 |
|---|---|
| Distinct (%) | 100.0% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 445.6173815 |
| Minimum | 1 |
|---|---|
| Maximum | 891 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 45.25 |
| Q1 | 223.25 |
| median | 445.5 |
| Q3 | 666.75 |
| 95-th percentile | 846.75 |
| Maximum | 891 |
| Range | 890 |
| Interquartile range (IQR) | 443.5 |
Descriptive statistics
| Standard deviation | 257.0487858 |
|---|---|
| Coefficient of variation (CV) | 0.5768374316 |
| Kurtosis | -1.195429246 |
| Mean | 445.6173815 |
| Median Absolute Deviation (MAD) | 222 |
| Skewness | 0.002397173832 |
| Sum | 394817 |
| Variance | 66074.0783 |
| Monotonicity | Strictly increasing |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 1 | 1 | 0.1% |
| 598 | 1 | 0.1% |
| 587 | 1 | 0.1% |
| 588 | 1 | 0.1% |
| 589 | 1 | 0.1% |
| 590 | 1 | 0.1% |
| 591 | 1 | 0.1% |
| 592 | 1 | 0.1% |
| 593 | 1 | 0.1% |
| 594 | 1 | 0.1% |
| Other values (876) | 876 |
| Value | Count | Frequency (%) |
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 |
| Value | Count | Frequency (%) |
| 891 | 1 | |
| 890 | 1 | |
| 889 | 1 | |
| 888 | 1 | |
| 887 | 1 | |
| 886 | 1 | |
| 885 | 1 | |
| 884 | 1 | |
| 883 | 1 | |
| 882 | 1 |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.0 KiB |
| 0 | |
|---|---|
| 1 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 886 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 1 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
Length
Histogram of lengths of the category
Category Frequency Plot
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 886 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 886 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 886 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 549 | |
| 1 | 337 |
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.3% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.0 KiB |
| 3 | |
|---|---|
| 1 | |
| 2 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 886 |
|---|---|
| Distinct characters | 3 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 3 |
|---|---|
| 2nd row | 1 |
| 3rd row | 3 |
| 4th row | 1 |
| 5th row | 3 |
Common Values
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Length
Histogram of lengths of the category
Category Frequency Plot
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 886 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 886 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 886 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 3 | 491 | |
| 1 | 211 | |
| 2 | 184 | 20.8% |
Age
Real number (ℝ)
| Distinct | 88 |
|---|---|
| Distinct (%) | 9.9% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 2.16531082 × 10-16 |
| Minimum | -2.222022385 |
|---|---|
| Maximum | 3.901957659 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 561 |
| Negative (%) | 63.3% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | -2.222022385 |
|---|---|
| 5-th percentile | -1.792620416 |
| Q1 | -0.5613602919 |
| median | -0.09963774526 |
| Q3 | 0.4390385591 |
| 95-th percentile | 1.901159957 |
| Maximum | 3.901957659 |
| Range | 6.123980043 |
| Interquartile range (IQR) | 1.000398851 |
Descriptive statistics
| Standard deviation | 1.000564812 |
|---|---|
| Coefficient of variation (CV) | 4.620883076 × 1015 |
| Kurtosis | 1.003223995 |
| Mean | 2.16531082 × 10-16 |
| Median Absolute Deviation (MAD) | 0.4617225466 |
| Skewness | 0.5120820931 |
| Sum | 2.011724121 × 10-13 |
| Variance | 1.001129944 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| -0.09963774526 | 202 | |
| -0.4074527763 | 30 | 3.4% |
| -0.5613602919 | 27 | 3.0% |
| -0.869175323 | 26 | 2.9% |
| -0.7922215652 | 25 | 2.8% |
| 0.05426977028 | 25 | 2.8% |
| -0.6383140497 | 24 | 2.7% |
| -0.3304990186 | 23 | 2.6% |
| 0.5159923169 | 21 | 2.4% |
| -0.02268398749 | 20 | 2.3% |
| Other values (78) | 463 |
| Value | Count | Frequency (%) |
| -2.222022385 | 1 | 0.1% |
| -2.202783945 | 1 | 0.1% |
| -2.196627645 | 2 | 0.2% |
| -2.190471344 | 2 | 0.2% |
| -2.183545506 | 1 | 0.1% |
| -2.177389205 | 7 | |
| -2.100435447 | 10 | |
| -2.02348169 | 6 | |
| -1.946527932 | 10 | |
| -1.869574174 | 4 | 0.5% |
| Value | Count | Frequency (%) |
| 3.901957659 | 1 | 0.1% |
| 3.440235112 | 1 | 0.1% |
| 3.209373839 | 2 | |
| 3.17089696 | 1 | 0.1% |
| 3.132420081 | 2 | |
| 2.82460505 | 1 | 0.1% |
| 2.747651292 | 3 | |
| 2.670697534 | 2 | |
| 2.593743777 | 2 | |
| 2.516790019 | 3 |
| Distinct | 7 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.5259593679 |
| Minimum | 0 |
|---|---|
| Maximum | 8 |
| Zeros | 603 |
| Zeros (%) | 68.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 1 |
| 95-th percentile | 3 |
| Maximum | 8 |
| Range | 8 |
| Interquartile range (IQR) | 1 |
Descriptive statistics
| Standard deviation | 1.105151233 |
|---|---|
| Coefficient of variation (CV) | 2.101210284 |
| Kurtosis | 17.77682411 |
| Mean | 0.5259593679 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 3.684609408 |
| Sum | 466 |
| Variance | 1.221359248 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 603 | |
| 1 | 209 | 23.6% |
| 2 | 28 | 3.2% |
| 4 | 18 | 2.0% |
| 3 | 16 | 1.8% |
| 8 | 7 | 0.8% |
| 5 | 5 | 0.6% |
| Value | Count | Frequency (%) |
| 0 | 603 | |
| 1 | 209 | 23.6% |
| 2 | 28 | 3.2% |
| 3 | 16 | 1.8% |
| 4 | 18 | 2.0% |
| 5 | 5 | 0.6% |
| 8 | 7 | 0.8% |
| Value | Count | Frequency (%) |
| 8 | 7 | 0.8% |
| 5 | 5 | 0.6% |
| 4 | 18 | 2.0% |
| 3 | 16 | 1.8% |
| 2 | 28 | 3.2% |
| 1 | 209 | 23.6% |
| 0 | 603 |
| Distinct | 7 |
|---|---|
| Distinct (%) | 0.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.3826185102 |
| Minimum | 0 |
|---|---|
| Maximum | 6 |
| Zeros | 674 |
| Zeros (%) | 76.1% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | 0 |
|---|---|
| 5-th percentile | 0 |
| Q1 | 0 |
| median | 0 |
| Q3 | 0 |
| 95-th percentile | 2 |
| Maximum | 6 |
| Range | 6 |
| Interquartile range (IQR) | 0 |
Descriptive statistics
| Standard deviation | 0.807655689 |
|---|---|
| Coefficient of variation (CV) | 2.110864131 |
| Kurtosis | 9.734674532 |
| Mean | 0.3826185102 |
| Median Absolute Deviation (MAD) | 0 |
| Skewness | 2.744455451 |
| Sum | 339 |
| Variance | 0.6523077119 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 674 | |
| 1 | 117 | 13.2% |
| 2 | 80 | 9.0% |
| 5 | 5 | 0.6% |
| 3 | 5 | 0.6% |
| 4 | 4 | 0.5% |
| 6 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 0 | 674 | |
| 1 | 117 | 13.2% |
| 2 | 80 | 9.0% |
| 3 | 5 | 0.6% |
| 4 | 4 | 0.5% |
| 5 | 5 | 0.6% |
| 6 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 6 | 1 | 0.1% |
| 5 | 5 | 0.6% |
| 4 | 4 | 0.5% |
| 3 | 5 | 0.6% |
| 2 | 80 | 9.0% |
| 1 | 117 | 13.2% |
| 0 | 674 |
| Distinct | 246 |
|---|---|
| Distinct (%) | 27.8% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 1.383393024 × 10-16 |
| Minimum | -0.7407918193 |
|---|---|
| Maximum | 5.653180587 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 659 |
| Negative (%) | 74.4% |
| Memory size | 7.0 KiB |
Quantile statistics
| Minimum | -0.7407918193 |
|---|---|
| 5-th percentile | -0.5651399158 |
| Q1 | -0.5488316394 |
| median | -0.3893859032 |
| Q3 | 0.004284656837 |
| 95-th percentile | 1.954967726 |
| Maximum | 5.653180587 |
| Range | 6.393972406 |
| Interquartile range (IQR) | 0.5531162962 |
Descriptive statistics
| Standard deviation | 1.000564812 |
|---|---|
| Coefficient of variation (CV) | 7.232686554 × 1015 |
| Kurtosis | 12.13091898 |
| Mean | 1.383393024 × 10-16 |
| Median Absolute Deviation (MAD) | 0.1678527159 |
| Skewness | 3.204136704 |
| Sum | 1.151301277 × 10-13 |
| Variance | 1.001129944 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| -0.545082778 | 43 | 4.9% |
| -0.4247399514 | 42 | 4.7% |
| -0.5488316394 | 38 | 4.3% |
| -0.5523762827 | 34 | 3.8% |
| -0.1086880834 | 31 | 3.5% |
| -0.4855191567 | 24 | 2.7% |
| -0.5481217383 | 18 | 2.0% |
| -0.5517684906 | 16 | 1.8% |
| -0.5650378067 | 15 | 1.7% |
| -0.7407918193 | 15 | 1.7% |
| Other values (236) | 610 |
| Value | Count | Frequency (%) |
| -0.7407918193 | 15 | |
| -0.6432411947 | 1 | 0.1% |
| -0.6192334086 | 1 | 0.1% |
| -0.5891477019 | 1 | 0.1% |
| -0.5842853655 | 1 | 0.1% |
| -0.5839814695 | 1 | 0.1% |
| -0.5828679944 | 2 | 0.2% |
| -0.5766879648 | 2 | 0.2% |
| -0.5740550096 | 1 | 0.1% |
| -0.5718256284 | 1 | 0.1% |
| Value | Count | Frequency (%) |
| 5.653180587 | 4 | |
| 5.637985785 | 2 | |
| 5.276855196 | 2 | |
| 4.790723662 | 4 | |
| 4.651033599 | 1 | 0.1% |
| 4.401128956 | 1 | 0.1% |
| 4.397178308 | 3 | |
| 3.267394989 | 2 | |
| 2.990139703 | 3 | |
| 2.943643611 | 4 |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.0 KiB |
| 0 | |
|---|---|
| 1 | 77 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 886 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
Length
Histogram of lengths of the category
Category Frequency Plot
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 886 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 886 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 886 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 809 | |
| 1 | 77 | 8.7% |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.0 KiB |
| 1 | |
|---|---|
| 0 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 886 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 1 |
|---|---|
| 2nd row | 0 |
| 3rd row | 1 |
| 4th row | 1 |
| 5th row | 1 |
Common Values
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
Length
Histogram of lengths of the category
Category Frequency Plot
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
Most occurring characters
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 886 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 886 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 886 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 1 | 644 | |
| 0 | 242 | 27.3% |
| Distinct | 2 |
|---|---|
| Distinct (%) | 0.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 7.0 KiB |
| 1 | |
|---|---|
| 0 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 886 |
|---|---|
| Distinct characters | 2 |
| Distinct categories | 1 ? |
| Distinct scripts | 1 ? |
| Distinct blocks | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 1 |
|---|---|
| 2nd row | 0 |
| 3rd row | 0 |
| 4th row | 0 |
| 5th row | 1 |
Common Values
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Length
Histogram of lengths of the category
Category Frequency Plot
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Most occurring characters
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 886 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 886 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 886 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 1 | 575 | |
| 0 | 311 |
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here. A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
First rows
| df_index | PassengerId | Survived | Pclass | Age | SibSp | Parch | Fare | Embarked_Q | Embarked_S | Sex_male | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 1 | 0 | 3 | -0.561360 | 1 | 0 | -0.564532 | 0 | 1 | 1 |
| 1 | 1 | 2 | 1 | 1 | 0.669900 | 1 | 0 | 0.992225 | 0 | 0 | 0 |
| 2 | 2 | 3 | 1 | 3 | -0.253545 | 0 | 0 | -0.548122 | 0 | 1 | 0 |
| 3 | 3 | 4 | 1 | 1 | 0.439039 | 1 | 0 | 0.550159 | 0 | 1 | 0 |
| 4 | 4 | 5 | 0 | 3 | 0.439039 | 0 | 0 | -0.545083 | 0 | 1 | 1 |
| 5 | 5 | 6 | 0 | 3 | -0.099638 | 0 | 0 | -0.535156 | 1 | 0 | 1 |
| 6 | 6 | 7 | 0 | 1 | 1.901160 | 0 | 0 | 0.520073 | 0 | 1 | 1 |
| 7 | 7 | 8 | 0 | 3 | -2.100435 | 3 | 1 | -0.228423 | 0 | 1 | 1 |
| 8 | 8 | 9 | 1 | 3 | -0.176592 | 0 | 2 | -0.470123 | 0 | 1 | 0 |
| 9 | 9 | 10 | 1 | 2 | -1.176990 | 1 | 0 | -0.009720 | 0 | 0 | 0 |
Last rows
| df_index | PassengerId | Survived | Pclass | Age | SibSp | Parch | Fare | Embarked_Q | Embarked_S | Sex_male | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 876 | 881 | 882 | 0 | 3 | 0.285131 | 0 | 0 | -0.548832 | 0 | 1 | 1 |
| 877 | 882 | 883 | 0 | 3 | -0.561360 | 0 | 0 | -0.485113 | 0 | 1 | 0 |
| 878 | 883 | 884 | 0 | 2 | -0.099638 | 0 | 0 | -0.485519 | 0 | 1 | 1 |
| 879 | 884 | 885 | 0 | 3 | -0.330499 | 0 | 0 | -0.569394 | 0 | 1 | 1 |
| 880 | 885 | 886 | 0 | 3 | 0.746854 | 0 | 5 | -0.032714 | 1 | 0 | 0 |
| 881 | 886 | 887 | 0 | 2 | -0.176592 | 0 | 0 | -0.424740 | 0 | 1 | 1 |
| 882 | 887 | 888 | 1 | 1 | -0.792222 | 0 | 0 | -0.011441 | 0 | 1 | 0 |
| 883 | 888 | 889 | 0 | 3 | -0.099638 | 1 | 2 | -0.170683 | 0 | 1 | 0 |
| 884 | 889 | 890 | 1 | 1 | -0.253545 | 0 | 0 | -0.011441 | 0 | 0 | 1 |
| 885 | 890 | 891 | 0 | 3 | 0.208177 | 0 | 0 | -0.552376 | 1 | 0 | 1 |